This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Aharon, N., Orfaig, R., Bobrovsky, B.-Z. (2022) BoT-SORT: Robust associations multi-pedestrian tracking. ArXiv, abs/2206.14651.Search in Google Scholar
Akyon, F.C., Altinuc, S.O., Temizel, A. (2022) Slicing aided hyper inference and fine-tuning for small object detection. In: Proceedings of IEEE International Conference on Image Processing (ICIP), Bordeaux, October 2022. IEEE, pp. 966-970. https://doi.org/10.1109/ICIP46576.2022.9897990.Search in Google Scholar
Džunda, M., Dzurovčin, P., Melníková, L. (2022) Anti-collision system for small civil aircraft. Applied Sciences, 12(3), 1648. https://doi.org/10.3390/APP12031648.Search in Google Scholar
Fursich, B., Bamler, R., Augustin, S., Hubers, H.W., Zhu, X.X. (2016) Towards single-pixel FMCW radar reconstruction. In: Proceedings of 4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing (CoSeRa), Aachen, September 2016. IEEE, pp. 95–99. https://doi.org/10.1109/COSERA.2016.7745707.Search in Google Scholar
Hu, M., Li, Z., Yu, J., Wan, X., Tan, H., Lin, Z. (2023) Efficient-lightweight YOLO: Improving small object detection in YOLO for aerial images. Sensors, 23(14), 6423. https://doi.org/10.3390/S23146423.Search in Google Scholar
Huo, Z., Yan, T., Cao, W. (2021) Fast small object detection algorithm based on feature enhancement and reconstruction. In: Proceedings of 13th International Conference on Wireless Communications and Signal Processing (WCSP), Changsha, October 2021. IEEE, 1-5. https://doi.org/10.1109/WCSP52459.2021.9613660.Search in Google Scholar
Federal Aviation Administration. (2011) Introduction to TCAS II Version 7.1. U.S. Department of Transportation.Search in Google Scholar
Jabłoński, B., Makowski, D., Perek, P., Nowakowski, P.N.V., Sitjes, A.P., Jakubowski, M., Gao, Y., Winter, A. (2022) Evaluation of NVIDIA Xavier NX platform for real-time image processing for plasma diagnostics. Energies, 15(6), 2088. https://doi.org/10.3390/EN15062088Search in Google Scholar
Kateb, F.A., Monowar, M.M., Hamid, M.A., Ohi, A.Q., Mridha, M.F. (2021) FruitDet: Attentive feature aggregation for real-time fruit detection in orchards. Agronomy, 11(12), 2440. https://doi.org/10.3390/AGRONOMY11122440Search in Google Scholar
Kulisz, M., Kłosowski, G., Rymarczyk, T., Hoła, A., Niderla, K., Sikora, J. I. (2024) The use of the multi-sequential LSTM in electrical tomography for masonry wall moisture detection. Measurement, 234, 114860. https://doi.org/10.1016/J.MEASUREMENT.2024.114860.Search in Google Scholar
Lin, T.-Y., Maire, M., Belongie, S., Bourdev, L., Girshick, R., Hays, J., Perona, P., Ramanan, D., Zitnick, C.L., Dolí, P. (2014) Microsoft COCO: Common objects in context. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds) Computer Vision – ECCV 2014. ECCV 2014. Lecture Notes in Computer Science, 8693. Springer, Cham. https://doi.org/10.1007/978-3-319-10602-1_48.Search in Google Scholar
Liu, S., Huang, D., Wang, Y. (2019) Learning spatial fusion for single-shot object detection. 10.48550/arXiv.1911.09516.Search in Google Scholar
Maas, J., van Gent, R., Hoekstra, J. (2020) A portable primary radar for general aviation. PLoS One, 15(10), e0239892. https://doi.org/10.1371/JOURNAL.PONE.0239892.Search in Google Scholar
PyTorch (2024) PyTorch Foundation. Available at https://pytorch.org/ (accessed 10.18.24).Search in Google Scholar
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B. (2021) High-resolution image synthesis with latent diffusion models. In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), New Orleans, LA, USA, June 2022. IEEE, 10674-10685. https://doi.org/10.1109/CVPR52688.2022.01042.Search in Google Scholar
Smyers, E.Q., Katz, S.M., Corso, A.L., Kochenderfer, M.J. (2023) AVOIDDS: Aircraft vision-based intruder detection dataset and simulator. Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track. https://doi.org/10.48550/arXiv.2306.11203.Search in Google Scholar
Tan, M., Pang, R., Le, Q. V. (2020) EfficientDet: Scalable and efficient object detection. In: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, June 2020. IEEE, pp. 10778-10787. https://doi.org/10.1109/CVPR42600.2020.01079.Search in Google Scholar
Tang, J. (2017) Review: Analysis and improvement of traffic alert and collision avoidance system. IEEE Access, 5, 21419–21429. https://doi.org/10.1109/ACCESS.2017.2757598.Search in Google Scholar
Terven, J.R., Cordova-Esparza, D.M. (2023) A comprehensive review of YOLO architectures in computer vision: From YOLOv1 to YOLOv8 and YOLO-NAS. Machine Learning and Knowledge Extraction, 5(4), 1680-1716. https://doi.org/10.3390/make5040083.Search in Google Scholar
Tong, K., Wu, Y. (2024) I-YOLO: A novel single-stage framework for small object detection. The Visual Computer, 40(12). doi: 8927-8944. 10.1007/s00371-024-03284-8.Search in Google Scholar
Yang, G., Lei, J., Zhu, Z., Cheng, S., Feng, Z., Liang, R. (2023) AFPN: Asymptotic feature pyramid network for object detection. In: Proceedings of IEEE International Conference on Systems, Man, and Cybernetics (SMC), Honolulu, October 2023. IEEE, 2184-2189. https://doi.org/10.1109/SMC53992.2023.10394415.Search in Google Scholar
Yang, Z., Kang, X., Gong, Y., Wang, J. (2023) Aircraft trajectory prediction and aviation safety in ADS-B failure conditions based on neural network. Scientific Reports, 13, 19677. https://doi.org/10.1038/s41598-023-46914-2.Search in Google Scholar
Zhai, X., Huang, Z., Li, T., Liu, H., Wang, S. (2023) YOLO-drone: An optimized YOLOv8 network for tiny UAV object detection. Electronics, 12(17), 3664. https://doi.org/10.3390/ELECTRONICS12173664.Search in Google Scholar